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dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
The GWAS Catalog is an open access repository of all human genome wide association studies. It is considered the “go-to” resource for genetic evidence of associations between common genetic variation and diseases or phenotypes, is accessed by scientists, clinicians and other users worldwide, and is integrated with numerous other resources. Association data and metadata are identified and extracted from the scientific literature by expert data curators. Submissions of full genome wide summary data can be made directly by authors, either before or after journal publication.
The Neuroscience Information Framework is a dynamic index of data, materials, and tools. Please note, we do not accept direct data deposits, but if you wish to make your data repository or database available through our search, please contact us. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.
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The repository is no longer available. <<<!!!<<< Visit IRIS at EPA: https://www.epa.gov/iris >>>!!!>>>
Brain Analysis Library of Spatial maps and Atlases (BALSA) is a database for hosting and sharing neuroimaging and neuroanatomical datasets for human and primate species. BALSA houses curated, user-created Study datasets, extensively analyzed neuroimaging data associated with published figures and Reference datasets mapped to brain atlas surfaces and volumes in human and nonhuman primates as a general resource (e.g., published cortical parcellations).
<<<!!!<<< The page is no longer available. This database was already retired, and on this page users could find information on how to search and use these sequences. dbSTS was an NCBI resource that contained sequence data for short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. >>>!!!>>>
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.